plot_ly(dfmodel, x=~food,color=~dish)
## No trace type specified:
## Based on info supplied, a 'histogram' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#histogram
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
plot_ly(dfmodel, x=~casserole, y=~mean,color=~food)
## No trace type specified:
## Based on info supplied, a 'bar' trace seems appropriate.
## Read more about this trace type -> https://plotly.com/r/reference/#bar
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
food <- ggplot(dfmodel,aes(x=mean,fill=food, frame=before_or_after, alpha=.07)) +
geom_density()
ggplotly(food)
dish <- ggplot(dfmodel,aes(x=mean,fill=dish, frame=before_or_after, alpha=.07)) +
geom_density()
ggplotly(dish)
argued <- ggplot(dfmodel,aes(x=mean,fill=argued, frame=before_or_after, alpha=.07)) +
geom_density()
ggplotly(argued)
test2 <- ggplot(dfmodel,aes(x=casserole,y=mean, fill=casserole))+
geom_boxplot()#+
geom_point(aes(x=mean))
## mapping: x = ~mean
## geom_point: na.rm = FALSE
## stat_identity: na.rm = FALSE
## position_identity
ggplotly(test2)
library(ggridges)
ggplot(dfmodel,aes(y=casserole,x=mean, fill=casserole))+
geom_density_ridges()
## Picking joint bandwidth of 0.305
